2015-03-03T10:45:08ZOn optimal two-level supersaturated designshttp://dspace.library.iitb.ac.in/jspui/handle/100/17349
Title: On optimal two-level supersaturated designs
Authors: Singh, Rakhi; Das, Ashish
Abstract: A popular measure to assess two-level supersaturated designs is the $E(s^2)$ criteria. Recently, Jones and Majumdar (2014) introduced the $\mbox{{\it UE}}(s^2)$ criteria and obtained optimal designs under the criteria. Effect-sparsity principle states that only a very small proportion of the factors have effects that are large. These factors with large effects are called {\it active} factors. Therefore, the basis of using a supersaturated design is the inherent assumption that there are very few active factors which one has to identify. Though there are only a few active factors, it is not known a priori what these active factors are. The identification of the active factors, say $k$ in number, is based on model building regression diagnostics (e.g. forward selection method) wherein one has to desirably use a supersaturated design which on an average estimates the model parameters optimally during the sequential introduction of factors in the model building process. Accordingly, to overcome possible lacuna on existing criteria of measuring the goodness of a supersaturated design, we meaningfully define the $ave(s^2_k)$ and $ave(s^2)_\rho$ criteria, where $\rho$ is the maximum number of active factors. We obtain superior $\mbox{{\it UE}}(s^2)$-optimal designs in ${\cal D}_U(m,n)$ and compare them against $E(s^2)$-optimal designs under the more meaningful criteria of $ave(s^2_k)$ and $ave(s^2)_\rho$. It is seen that $E(s^2)$-optimal designs perform fairly well or better even against superior $\mbox{{\it UE}}(s^2)$-optimal designs with respect to $ave(s^2_k)$ and $ave_d(s^2)_\rho$ criteria.2015-02-04T00:00:00ZMultipronged quantitative proteomic analyses indicate modulation of various signal transduction pathways in human meningiomashttp://dspace.library.iitb.ac.in/jspui/handle/100/17348
Title: Multipronged quantitative proteomic analyses indicate modulation of various signal transduction pathways in human meningiomas
Authors: SHARMA, S; RAY, SANDIPAN; MUKHERJEE, SHUVOLINA; MOIYADI, ALIASGAR; SRIDHAR, EPARI; SRIVASTAVA, SANJEEVA
Abstract: Meningiomas (MGs) are frequent tumors of the CNS originating from the meningeal layers of the spinal cord and the brain. In this study, comparative tissue proteomic analysis of low and high grades of MGs was performed by using iTRAQ-based quantitative proteomics in combination with ESI-quadrupole-TOF and Q-Exactive MS, and results were validated by employing ELISA. Combining the results obtained from two MS platforms, we were able to identify overall 4308 proteins (1% false discover rate), among which 2367 exhibited differential expression (more than and equal to 2 peptide and ≥1.5-fold in at least one grade) in MGs. Several differentially expressed proteins were found to be associated with diverse signaling pathways, including integrin, Wnt, Ras, epidermal growth factor receptor, and FGR signaling. Proteins, such as vinculin or histones, which act as the signaling activators to initiate multiple signaling pathways, were found to be upregulated in MGs. Quite a few candidates, such as protein S-100A6, aldehyde dehydrogenase mitochondrial, AHNAK, cytoskeleton-associated protein 4, and caveolin, showed sequential increase in low- and high-grade MGs, whereas differential expressions of collagen alpha-1 (VI), protein S100-A9, 14 kDa phosphohistidine phosphatase, or transgelin-2 were found to be grade specific. Our findings provide new insights regarding the association of various signal transduction pathways in MG pathogenesis and may introduce new opportunities for the early detection and prognosis of MGs.2015-01-01T00:00:00ZQuantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markershttp://dspace.library.iitb.ac.in/jspui/handle/100/17347
Title: Quantitative Proteomic Analysis of Meningiomas for the Identification of Surrogate Protein Markers
Authors: SHARMA, S; RAY, S; MOIYADI, A; SRIDHAR, E; SRIVASTAVA, S
Abstract: Meningiomas are the most common non-glial tumors of the brain and spine. Pathophysiology and definite histological grading of meningiomas are frequently found to be deceptive due to their unusual morphological features and locations. Here for the first time we report a comprehensive serum proteomic analysis of different grades of meningiomas by using multiple quantitative proteomic and immunoassay-based approaches to obtain mechanistic insights about disease pathogenesis and identify grade specific protein signatures. In silico functional analysis revealed modulation of different vital physiological pathways including complement and coagulation cascades, metabolism of lipids and lipoproteins, immune signaling, cell growth and apoptosis and integrin signaling in meningiomas. ROC curve analysis demonstrated apolipoprotein E and A-I and hemopexin as efficient predictors for meningiomas. Identified proteins like vimentin, alpha-2-macroglobulin, apolipoprotein B and A-I and antithrombin-III, which exhibited a sequential increase in different malignancy grades of meningiomas, could serve as potential predictive markers.2014-01-01T00:00:00ZAcceleration of the polymerization of rodlike molecules by flowhttp://dspace.library.iitb.ac.in/jspui/handle/100/17346
Title: Acceleration of the polymerization of rodlike molecules by flow
Authors: AGGE, A; JAIN, S; KHAKHAR, DV
Abstract: Polymerization of rigid rodlike molecules with reactive end groups (e.g., poly(p-phenylene terephthalamide)) requires near parallel orientation of the molecules. The reaction becomes diffusion-limited as the rotational diffusivity of the reacting molecules decreases to low values in the later stages of the reaction, and this ultimately limits the molecular weight of the polymers formed. Here a theoretical study of the step-growth reaction between rodlike molecules in a solution under extensional flow is carried out. A model for the process is developed using the Smoluchowski approach which yields the effective reaction rate constant for the process in terms of the system parameters. The rate of reaction increases with extensional rate because of flow-induced orientation of molecules, and for sufficiently high extensional rates, the rate constant becomes higher than the intrinsic value. This is an instance where flow has a catalyst-like effect on the reaction. The results indicate that flow can be a useful tool for accelerating reactions and thus improving yield and selectivity for orientation-dependent reactions between large anisotropic molecules.2000-01-01T00:00:00Z